Business Statistics

470 Business Statistics

Error sum of squares (SSE) is the sum of squared differences between each observed value (y

i

) and

regressed (predicted) value of

y.

Error sum of squares = (SSE) =

2

ˆ

( )−

∑

i i

y y

Figure 14.19 exhibits the measures of variation in simple linear regression. It can be seen easily

that Total sum of squares (SST)

= regression sum of squares (SSR) + error sum of squares (SSE), that

is, 138,966.6667(SST) = 125,197.4582 (SSR) +13,769.20842 (SSE)

Figure 14.20 is the ANOVA table produced using MS Excel exhibiting values of SST, SSR and

SSE and other values for Example 14.1. The same ANOVA table as shown in Figure 14.20 can be

obtained ...